Thomas Brox
Thomas Brox | |
|---|---|
 Brox in 2020 | |
| Born | 1976 (age 49–50) |
| Education | Saarland University |
| Awards | Longuet-Higgins Best Paper Award (2004) Koenderink Prize (2014) |
| Scientific career | |
| Fields | Computer vision, machine learning |
| Workplaces | University of Freiburg |
Thomas Brox (born 1976) is a computer scientist and professor of pattern recognition and image processing at the University of Freiburg, where he heads the Computer Vision Group.[1] His research is in computer vision and machine learning, including optical flow, visual representation learning and deep neural networks.[1] He co-authored the U-Net architecture for biomedical image segmentation and FlowNet, a convolutional-neural-network approach to optical-flow estimation.[2][3] According to Scopus, Brox's publications had received more than 130,000 citations by 2026.[4]
Research on optical-flow estimation that Brox published with Andrés Bruhn, Nils Papenberg and Joachim Weickert received the Longuet-Higgins Best Paper Award at the European Conference on Computer Vision (ECCV) in 2004 and the Koenderink Prize in 2014.[5] Brox has been a full member of the Heidelberg Academy of Sciences and Humanities since 2020.[6]
Academic career
[edit]Brox received his doctorate in computer science from Saarland University in 2005. He subsequently worked as a postdoctoral researcher at the University of Bonn, headed the Intelligent Systems Group at TU Dresden as a temporary professor, and was a postdoctoral researcher in Jitendra Malik's computer vision group at the University of California, Berkeley. In 2010, he joined the University of Freiburg, where he became professor of pattern recognition and image processing and head of the Computer Vision Group.[1]
Brox was one of the programme chairs of ECCV 2020.[5] On 1 July 2026, he became dean of the University of Freiburg's Faculty of Engineering.[7]
Research
[edit]An early focus of Brox's research was optical flow, the estimation of apparent motion between images. In 2004, Brox, Bruhn, Papenberg and Weickert proposed a variational optical-flow method combining brightness and gradient constancy with a discontinuity-preserving smoothness constraint and a nonlinear, multi-resolution optimization scheme.[8] The work received the Longuet-Higgins Best Paper Award at ECCV 2004 and, ten years later, the Koenderink Prize.[5]
In 2015, Brox co-authored two deep learning approaches in computer vision. With Olaf Ronneberger and Philipp Fischer, he presented U-Net, a convolutional architecture for biomedical image segmentation that combines a contracting path with an expanding path for spatial localization, including skip connections to carry forward, high-resolution information from the encoder.[2]
In the same year, Brox was a co-author of FlowNet, which formulated optical-flow estimation as a supervised learning problem for convolutional neural networks and used entirely synthetically generated training data.[3]
Awards and memberships
[edit]References
[edit]- 1 2 3 "Thomas Brox". Computer Vision Group. University of Freiburg. Retrieved 1 September 2026.
- 1 2 Ronneberger, Olaf; Fischer, Philipp; Brox, Thomas (2015). "U-Net: Convolutional Networks for Biomedical Image Segmentation". Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. Lecture Notes in Computer Science. Vol. 9351. Springer. pp. 234–241. doi:10.1007/978-3-319-24574-4_28.
- 1 2 Dosovitskiy, Alexey; Fischer, Philipp; Ilg, Eddy; Häusser, Philip; Hazırbaş, Caner; Golkov, Vladimir; van der Smagt, Patrick; Cremers, Daniel; Brox, Thomas (2015). "FlowNet: Learning Optical Flow with Convolutional Networks". Proceedings of the IEEE International Conference on Computer Vision. pp. 2758–2766. doi:10.1109/ICCV.2015.316.
- ↑ "Thomas Brox". ScienceDirect. Elsevier. Retrieved 1 September 2026.
- 1 2 3 4 5 "ECCV Awards". European Computer Vision Association. European Computer Vision Association. Retrieved 1 September 2026.
- 1 2 "Thomas Brox". Heidelberg Academy of Sciences and Humanities. Retrieved 1 September 2026.
- ↑ "Change at the Top of the Faculty of Engineering". Faculty of Engineering. University of Freiburg. Retrieved 1 September 2026.
- ↑ Brox, Thomas; Bruhn, Andrés; Papenberg, Nils; Weickert, Joachim (2004). "High Accuracy Optical Flow Estimation Based on a Theory for Warping". Computer Vision – ECCV 2004. Lecture Notes in Computer Science. Vol. 3024. Springer. pp. 25–36. doi:10.1007/978-3-540-24673-2_3.
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